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whisper-tiny-finetuned-en-transcribe – AI Model by jalal-elzein | AlphaNeural AI
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jalal-elzein
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whisper-tiny-finetuned-en-transcribe
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
PolyAI/minds14
openai/whisper-tiny
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-tiny-finetuned-en-transcribe
This model is a fine-tuned version of
openai/whisper-tiny
on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
Loss: 0.6964
Wer Ortho: 0.3436
Wer: 0.3430
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 500
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.0003
17.24
500
0.6964
0.3436
0.3430
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3
